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Title: Removing Diurnal Signals and Longer Term Trends From Electron Flux and ULF Correlations: A Comparison of Spectral Subtraction, Simple Differencing, and ARIMAX Models
Abstract

Simultaneously cycling space weather parameters may show high correlations even if there is no immediate relationship between them. We successfully remove diurnal cycles using spectral subtraction, and remove both diurnal and longer cycles (e.g., the 27 days solar cycle) with a difference transformation. Other methods of diurnal cycle removal (daily averaging, moving averages [MAs], and simpler spectral subtraction using regression) are less successful at removing cycles. We apply spectral subtraction (a finite impulse response equiripple bandstop filter) to hourly electron flux (Los Alamos National Laboratory satellite data) and a ground‐based ULF index to remove a 24 hr noise signal. This results in smoother time series appropriate for short‐term (approximately < 1 week) correlation and observational studies. However, spectral subtraction may not remove longer cycles such as the 27 days and 11 yr solar cycles. A differencing transformation (ytyt−24) removes not only the 24 hr noise signal but also the 27 days solar cycle, autocorrelation, and longer trends. This results in a low correlation between electron flux and the ULF index over long periods of time (maximum of 0.1). Correlations of electron flux and the ULF index with solar wind velocity (differenced atytyt−1) are also lower than previously reported (≤0.1). An autoregressive, MA transfer function model (ARIMAX) shows that there are significant cumulative effects of solar wind velocity on ULF activity over long periods, but correlations of velocity and ULF waves with flux are only seen over shorter time spans of more homogeneous geomagnetic activity levels.

 
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Award ID(s):
2013648
NSF-PAR ID:
10376010
Author(s) / Creator(s):
 ;  ;  
Publisher / Repository:
DOI PREFIX: 10.1029
Date Published:
Journal Name:
Journal of Geophysical Research: Space Physics
Volume:
127
Issue:
2
ISSN:
2169-9380
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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